English
 
Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

Evaluating the productivity of four main tree species in Germany under climate change with static reduced models

Authors
/persons/resource/Martin.Gutsch

Gutsch,  Martin
Potsdam Institute for Climate Impact Research;

/persons/resource/Petra.Lasch

Lasch-Born,  Petra
Potsdam Institute for Climate Impact Research;

/persons/resource/Felicitas.Suckow

Suckow,  Felicitas
Potsdam Institute for Climate Impact Research;

/persons/resource/Reyer

Reyer,  Christopher P. O.
Potsdam Institute for Climate Impact Research;

External Ressource
No external resources are shared
Fulltext (public)
There are no public fulltexts stored in PIKpublic
Supplementary Material (public)
There is no public supplementary material available
Citation

Gutsch, M., Lasch-Born, P., Suckow, F., Reyer, C. P. O. (2016): Evaluating the productivity of four main tree species in Germany under climate change with static reduced models. - Annals of Forest Science, 73, 2, 401-410.
https://doi.org/10.1007/s13595-015-0532-3


Cite as: https://publications.pik-potsdam.de/pubman/item/item_20525
Abstract
Key message We present simple models of forest net primary production (NPP) in Germany that show increasing productivity, especially in mountainous areas, under warming unless water becomes a limiting factor. They can be used for spatially explicit, rapid climate impact assessment. Context Climate impact studies largely rely on process-based forest models generally requiring detailed input data which are not everywhere available. Aims This study aims to derive simple models with low data requirements which allow calculation of NPP and analysis of climate impacts using many climate scenarios at a large amount of sites. Methods We fitted regression functions to the output of simulation experiments conducted with the process-based forest model 4C at 2342 climate stations in Germany for four main tree species on four different soil types and two time periods, 1951–2006 and 2031–2060. Results The regression functions showed a reasonable fit to measured NPP datasets. Temperature increase of up to 3 K leads to positive effects on NPP. In water-limited regions, this positive effect is dependent on the length of drought periods. The highest NPP increase occurs in mountainous regions. Conclusion Rapid analyses, using reduced models as presented here, can complement more detailed analyses with process-based models. Especially for dry sites, we recommend further study of climate impacts with process-based models or detailed measurements.